An adaptive interval type-2 fuzzy logic framework for classification of gait patterns of anterior cruciate ligament reconstructed subjects

This paper aims to investigate a gait pattern classification system for anterior cruciate ligament reconstructed (ACL-R) subjects based on the interval type-2 fuzzy logic (FL). The proposed system intends to model the uncertainties present in kinematics and electromyography (EMG) data used for gait analysis due to intra- and inter-subject stride-to-stride variability and nature of signals. Four features were selected from kinematics and EMG data recorded through wearable wireless sensors. The parameters for the membership functions of these input features were determined using the data recorded for 12 healthy and ACL-R subjects. The parameters for output membership functions and rules were chosen based on the recommendations from physiotherapists and physiatrists. The system was trained by using steepest descent method and tested for singleton and non-singleton inputs. The overall classification accuracy results show that the interval type-2 FL system outperforms the type-1 FL system in recognizing the gait patterns of healthy and ACL-R subjects.

[1]  N. Stergiou,et al.  Three-Dimensional Tibiofemoral Kinematics of the Anterior Cruciate Ligament-Deficient and Reconstructed Knee during Walking * , 2003, The American journal of sports medicine.

[2]  Hongyin Lau,et al.  The reliability of using accelerometer and gyroscope for gait event identification on persons with dropped foot. , 2008, Gait & posture.

[3]  John Scholz,et al.  Stride-to-stride variability of knee motion in patients with knee osteoarthritis. , 2006, Gait & posture.

[4]  Ahmet Yardimci,et al.  Fuzzy Logic Based Gait Classification for Hemiplegic Patients , 2007, IDA.

[5]  J. Mendel.  Uncertain Rule-Based Fuzzy Logic Systems: Introduction and New Directions , 2001 .

[6]  I. Sekiya,et al.  Arthroscopic evaluation of the articular cartilage after anterior cruciate ligament reconstruction: a short-term prospective study of 105 patients. , 2004, Arthroscopy : the journal of arthroscopic & related surgery : official publication of the Arthroscopy Association of North America and the International Arthroscopy Association.

[7]  N. Zheng,et al.  Alterations in three-dimensional joint kinematics of anterior cruciate ligament-deficient and -reconstructed knees during walking. , 2010, Clinical biomechanics.

[8]  Zi-Sheng Ai,et al.  Effect of anterior cruciate ligament reconstruction on biomechanical features of knee in level walking: a meta-analysis. , 2010, Chinese medical journal.

[9]  B. Freriks,et al.  Development of recommendations for SEMG sensors and sensor placement procedures. , 2000, Journal of electromyography and kinesiology : official journal of the International Society of Electrophysiological Kinesiology.

[10]  Maïté Brandt-Pearce,et al.  Neural Network Gait Classification for On-Body Inertial Sensors , 2009, 2009 Sixth International Workshop on Wearable and Implantable Body Sensor Networks.

[11]  Ramprasad Papannagari,et al.  In Vivo Kinematics of the Knee after Anterior Cruciate Ligament Reconstruction , 2006, The American journal of sports medicine.

[12]  James J Carollo,et al.  Effectiveness of Instrumented Gait Analysis in Children With Cerebral Palsy - Comparison of Outcomes , 2006, Journal of pediatric orthopedics.

[13]  R. Baker.  Gait analysis methods in rehabilitation , 2006, Journal of NeuroEngineering and Rehabilitation.

[14]  D. Theisen,et al.  Muscle strength and hop performance criteria prior to return to sports after ACL reconstruction , 2011, Knee Surgery, Sports Traumatology, Arthroscopy.

[15]  M. Axe,et al.  The effect of insufficient quadriceps strength on gait after anterior cruciate ligament reconstruction. , 2002, Clinical biomechanics.

[16]  R Begg,et al.  A machine learning approach for automated recognition of movement patterns using basic, kinetic and kinematic gait data. , 2005, Journal of biomechanics.

[17]  Kurt Manal,et al.  Gait and neuromuscular asymmetries after acute anterior cruciate ligament rupture. , 2012, Medicine and science in sports and exercise.

[18]  John Whyte,et al.  The Impact of Instrumented Gait Analysis on Surgical Planning: Treatment of Spastic Equinovarus Deformity of the Foot and Ankle , 2002, Foot & ankle international.

[19]  Hailong Zhu,et al.  Support vector machine for classification of walking conditions using miniature kinematic sensors , 2008, Medical & Biological Engineering & Computing.

[20]  J. Hart,et al.  Quadriceps activation following knee injuries: a systematic review. , 2010, Journal of athletic training.

[21]  J. Baumeister,et al.  Changed cortical activity after anterior cruciate ligament reconstruction in a joint position paradigm: an EEG study , 2007, Scandinavian journal of medicine & science in sports.

[22]  N. Stergiou,et al.  The effect of anterior cruciate ligament recontruction on lower extremity relative phase dynamics during walking and running , 2005 .

[23]  J. Nadal,et al.  Comparison of quadriceps and hamstrings activation ratio between healthy and anterior cruciate ligament reconstructed subjects , 2013, 2013 ISSNIP Biosignals and Biorobotics Conference: Biosignals and Robotics for Better and Safer Living (BRC).

[24]  D. Winter,et al.  EMG profiles during normal human walking: stride-to-stride and inter-subject variability. , 1987, Electroencephalography and clinical neurophysiology.

[25]  Adam L Bryant,et al.  Neuromuscular adaptations and correlates of knee functionality following ACL reconstruction , 2008, Journal of orthopaedic research : official publication of the Orthopaedic Research Society.